Relation between analyst reports and stock market prices (CD)

By: Gupta, Amit
Contributor(s): Nigam, Sarthak [Co-author] | Goswami, Shubham [Co-author]
Material type: Computer fileComputer filePublisher: Ahmedabad Indian Institute of Management Ahmedabad 2018Description: 18 p.: col. ill. Includes bibliographical referencesSubject(s): Analyst reports | Bayesian online changepoint | Latent Dirichlet allocation | Value analystsDDC classification: SP2018/2488 Online resources: e-Report Summary: This project aims to examine the correlation between analyst predictions and stock market prices. Analysts publish reports at regular intervals for many regularly traded stocks on the market. The stock prices can then follow the predictions of the report or move in a completely opposite direction. This project first tries to and out important points of change in the stock price data using a probabilistic change point method given by adams et. al [2]. The change points are then used as indicators of the analyst reports that need to be examined. The analyst reports are examined using a text analysis technique called Latent Dirichlet Allocation[3] that gets topics(a group of words with associated probabilities) from the reports. Finally, the similarity in these topics is analyzed to and out the extent to which analyst reports are able to predict the future performance of a stock.
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Student Project Vikram Sarabhai Library
Audio Visual
Non-fiction SP2018/2488 (Browse shelf) Not for Issue SP002488

Submitted to Prof. A. K. Laha
Submitted by PGP 2017-2019 batch in 5th term

This project aims to examine the correlation between analyst predictions and stock market prices. Analysts publish reports at regular intervals for many regularly traded stocks on the market. The stock prices can then follow the predictions of the report or move in a completely opposite direction. This project first tries to and out important points of change in the stock price data using a probabilistic change point method given by adams et. al [2]. The change points are then used as indicators of the analyst reports that need to be examined. The analyst reports are examined using a text analysis technique called Latent Dirichlet Allocation[3] that gets topics(a group of words with associated probabilities) from the reports. Finally, the similarity in these topics is analyzed to and out the extent to which analyst reports are able to predict the future performance of a stock.

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